Rating system, process and predictive algorithmic based medium for treatment of medical conditions and including workman compensation and general rehabilitation modules for optimizing care provider efficiencies and expedited treatment for achieving higher patient functional outcomes and lower cost

ABSTRACT

The present invention discloses a system, method and non-transitory software based computer writeable medium usable with a processor driven device for optimizing the diagnosis, treatment and resolution of worker injury events, such as associated with a workman compensation claim, and which improves upon the existing paper based module by synthesizing, in a digital environment, symptom, treatment and progress variables in a multi-party available format. A further related rehabilitation module, such as not limited to a worker injury event but also including any injury event associated with a typical accountable care organization (insurer/other payor/etc.) in a general health application is provided for establishing and tracking a patient&#39;s functional independent (FEM) measurement score. As with the workman compensation module, the rehabilitation module integrates the establishment of current conditions, achievable goals, and time based tracking of the patient treatment (including time elapsed changes in response to flat line response indicating a non-effective treatment plan) in order to define a patient goal outcome and to optimize real time treatment and progress tracking to that goal.

This application is a Continuation-in-part of application Ser. No.14/737,212 filed on Jun. 11, 2015. Application Ser. No. 14/737,212 is aContinuation-in-part of application Ser. No. 14/495,378 filed on Sep.24, 2014. Application Ser. No. 14/495,378 claims the benefit of U.S.Provisional Application 61/883,004 filed on Sep. 26, 2013, the contentsof which are incorporated herein in their entirety.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention is generally directed to financial-bio-psychosocial management models for optimal treatment of medical conditions.More particularly, the present invention discloses a system, processand, in particular, an improved algorithmic based non-transitorycomputer writeable medium for treatment of medical conditions in a costeffective fashion.

The system, process and associated algorithmic medium further includes arelated module for optimizing the diagnosis, treatment and resolution ofworker injury events, such as associated with a workman compensationclaim, and which improves upon the existing paper based module bysynthesizing, in a digital environment, symptom, treatment and progressvariables in a multi-party available format. In particular, the injuryevent module greatly increases care provider (physician) efficiency byintegrating and compiling electronically, in easily readable and timeelapsed formats, symptom and treatment variables. The moduleadditionally provides a reasonable and agreeable model, such as betweenthe employer/payer and worker, for establishing minimal goals forfacilitating return to work.

A further related rehabilitation module, such as not limited to a workerinjury event but also including any injury event associated with atypical accountable care organization (insurer/other payor/etc.) in ageneral health application is provided for establishing and tracking apatient's functional independent (FEM) measurement score. As with theworkman compensation module, the rehabilitation module integrates theestablishment of current conditions, achievable goals, and time basedtracking of the patient treatment (including time elapsed changes inresponse to flat line response indicating a non-effective treatmentplan) in order to define a patient goal outcome and to optimize realtime treatment and progress tracking to that goal.

In this fashion, the time frame between a worker injury event (or rehabsetting reported event) and an eventual agreed to return to work event(or final rehab setting event) is minimized through the maximization ofeffectiveness of the treatment protocols, as well as the maximization ofthe efficiency of the care provider by synthesizing into a simplifiedand time interval dynamic record the critical variables associated withthe treatment of the patient as derived from the best practices andcritical pathway modules and as integrated into these specificapplications.

Description of the Background Art

The prior art is documented with examples of systems and methods, suchas utilized in the medical field. A first example of this is set forthin Moore, U.S. Pat. No. 7,693,727 which teaches interactive systems andmethods for directing, integrating, documenting, and tracking stepstaken by medical providers during the process of care for a patient'sgiven condition. Doctors' actions are directed by a prescriptiveprotocol—a checklist of discrete steps designed for efficient or optimalcare of an individual patient's specific condition. The step-by-stepchecklist is abstracted from decision tree guidelines for the optimalwork up and treatment for the condition using probability-basedmethodology. The care protocols can be derived from widely available andnon-proprietary guidelines and decision trees based on public medicalresearch literature.

In one embodiment, the invention can be employed by a primary careclinician at the point of referral into the specialist sector, and atthe specialist level when proposing a risky or expensive or otherwiseproblematic medical or surgical diagnostic or treatment intervention. Atthese two critical transaction points in care, the checklist functionslike a lock, based on a hidden clinical decision algorithm (anexplanation of which can be displayed upon request). The system asks theclinician for data and then generates the patient's optimal checklist,displaying it as a point and click form keyed to the stage of care beingundertaken by each doctor. As the clinician enters data into thechecklist, a decision engine determines whether the checklist datasatisfies predetermined criteria for authorization of the proposedaction. The system can also document each transaction taken in theprocess of care to create an electronic record that can be madeaccessible to all clinicians involved in the process of care.

Moore, US 2004/0044546 teaches interactive methods and systems fordirecting, integrating, documenting and tracking steps taken by medicalproviders during the process of care for a given patient's condition.Doctors' actions are directed by a prescriptive protocol—a checklist ofdiscrete steps designed for efficient or optimal care of an individualpatient's specific condition. The step-by-step checklist is abstractedfrom decision tree guidelines for the optimal work up and treatment forthe condition using probability-based methodology. The care protocolscan be derived from widely available and non-proprietary guidelines anddecision trees based on public medical research literature.

In one embodiment, the invention can be employed by a primary careclinician at the point of referral into the specialist sector, and atthe specialist level when proposing a risky or expensive or otherwiseproblematic medical or surgical diagnostic or treatment intervention. Atthese two critical transaction points in care, the checklist functionslike a lock, based on a hidden clinical decision algorithm (anexplanation of which can be displayed upon request). The system asks theclinician for data and then generates the patient's optimal checklist,displaying it as a point and click form keyed to the stage of care beingundertaken by each doctor. As the clinician enters data into thechecklist, a decision engine determines whether the checklist datasatisfies predetermined criteria for authorization of the proposedaction. The system can also document each transaction taken in theprocess of care to create an electronic record that can be madeaccessible to all clinicians involved in the process of care.

A further example of the prior art is the healthcare providingorganization (HPO) model of Cusimano-Reaston et al., U.S. Pat. No.8,117,047, and which teaches a preferred provider network (PPO) or othermembership agreement that allows individuals or groups to join via amembership contract. The contract allows the HPO to provide a technicalcomponent of a medical evaluation or service. Additionally, the HPOemploys or retains the services of healthcare professionals whoparticipate in and monitor an evaluation of a patient who can be at aremote location from the healthcare professional. The HPO provides amedical diagnostic unit, which is known as an EFA-2, that allows thehealthcare professional to receive data that pertains to the patient viaa real-time communication protocol, or the patient data is collected andstored on an electronic storage device. The healthcare professional thenanalyzes the patient data and issues recommended treatment.

Lee, US 2012/0109689 teaches a support system for improved qualityhealthcare, defined as MEGICS (Medical+Logistics), developed in order toimprove quality of care and enhance the efficiency of operation ofhealthcare facilities and providers. When front-line healthcare doctorsand nurses make various clinical decisions, MEGICS management systemprovides them with relevant clinical knowledge in a timely manner withthe stated objective being to increase user satisfaction and providebetter quality of healthcare services.

Gliklich, U.S. Pat. No. 8,489,412, teaches a data processing system fordetermining clinical outcomes of medical data gathered by the system. Adoctor defines a medical study and can administer and collect datarelevant to that study in real time from potentially geographicallydiverse doctors, patients and other people associated with the study.The system can analyze the medical data in real-time according to anynumber of clinical algorithms that may be custom defined and editedbefore and during the study. The clinical algorithms produce clinicaloutcome data that can be used for treatment of patients participating inthe study immediately after the data is input and analyzed. The medicaloutcomes can indicate such things as performance comparisons, compositeoutcomes, and risk stratification and assessments for such things astreatments, drugs, illnesses, doctors, patients and physicians groups.

Mcllroy, U.S. Pat. No. 5,583,758, teaches a health care managementsystem for use by hospitals, physicians, insurance companies, healthmaintenance organizations, and others in the health care field includesa processing unit and health condition guidelines. A user inputsinformation related to the health condition of an individual andguideline treatment options are identified. The user also inputs actualor proposed and final recommendation treatments for the same individual.The resulting comparative information can be used to modify the actualor proposed treatment, or provide explanatory information as to reasonsfor the difference between the final recommendation treatment andguideline treatment options. Also, the comparative information can beused by a reviewer for evaluation or utilization purposes.

Goetzke, US 2003/0097185, discloses a medical resource for chronic painpatients forecasted using a method or computer software product toimprove accuracy in forecasting medical resources, decrease the timerequired to forecast medical resources, and many other benefits. Desiredpatient indicia including direct medical indicia, indirect medicalindicia, and non-medical indicia are selected to serve as independentvariables. At least one chronic pain indication is selected to serve asa dependent variable. A chronic pain forecasting model is created usingthe patient indicia and the chronic pain indication. The chronic painforecasting model is applied to a chronic pain patient indicia to createa patient forecast. Many different embodiments of the chronic painpatient dynamic medical resources forecaster method and software productare possible.

In summary, and while describing various systems, methods and protocolsfor attempting to optimize the efficiency of patient care, the prior artas a generalization acknowledges the inviolability of the presenthealthcare delivery model with its existing compensation and incentivestructures. These notably reward physicians and other medical providersbased on the quantum of care provided (e.g. tests conducted, surgicalprocedures performed, etc.) and as opposed to tying suchcompensation/incentives to documentable patient outcomes.

SUMMARY OF THE PRESENT INVENTION

The present invention provides a system, method and non-transitory andsoftware/algorithmic based computer writeable medium for revolutionizingthe delivery of healthcare, this primarily through the formulation andimplementation of results driven compensation/incentives to the provider(e.g. doctor, surgeon or other medical care professional), and asopposed to traditional compensation methods which reward such providerson the basis of quantum of care provided (tests ordered, surgicalprocedures conducted). The underpinnings of the present inventioninclude a central processor into which is loaded a best practices andcorresponding (financial) incentive database, the contents of which canbe promulgated or modified by a given payor or ACO (accountable careorganization).

In one variant, the non-transitory computer writeable mediumincorporates a predictive algorithm which includes a series of protocolsincluding a first protocol or subroutine for establishing a risk profilethrough stratifying a designated ACO population. A second protocol orsubroutine of the predictive algorithm further operates by training theACO doctors or other care providers in one or more of a series ofmedical related diagnosis and treatment programs (or disciplines) thesefurther potentially including but not limited to any one or more ofjoint, spine, cardiac, acute care, post-acute care, wound, vascular,cancer, diabetes, kidney, urology, pulmonary and vision care.

A third successive protocol/subroutine includes establishing one or moremanagement pathways which are customizable by the ACO leadership. Thisis accomplished through the establishing of a questioning protocol formodifying/customizing the base algorithm for any one or more of avariety of treatment sub-species and in order to establish subroutinesat this stage for any one or more of emergency care, immediate care,systemic complications, disability risk, psycho-social issues,preventive care and/or maintenance care.

A fourth protocol/subroutine provides care provider (e.g. doctor)feedback on the desired best practices for the given diagnosis andtreatment sub-species resulting from the question and answer protocolachieved in the third subroutine. A fifth protocol results in thecreation (again by the ACO or other provider) of a scorecard for eachindividual care provider (doctor, therapist, etc.), such based primarilyupon patient outcome assessment and accounting for patient complexities.In this fashion, shared savings resulting from the implementation of theprogram results are distributed based on the simplicity, transparencyand accountability provided by the present system and computer writeablemedium.

One non-limiting physical aspect of the present system includes theprovision of a patient kiosk (such loosely defined to include anypatient accessible input ranging from a physical station to a mobileapplication loaded into a smartphone or tablet computer) and whichpermits a patient to input necessary biographical and medically relevantinformation along with other information, the carrot for providing whichcan include additional benefits and enticements. A decision supportsystem interfaces with the processor and, in combination with additionalinformation inputs required by the service provider (e.g. physician,group of physicians or other designated care providing entity includinga hospital, clinic, etc.) formulates a provider scorecard for each suchindividual or entity which grades and rewards such providers based upontheir adherence to the best practice standards set by the ACO or otherpayor.

In this fashion, the present invention seeks to recalibrate theincentive structure of the care provider (such as further defined innon-limiting fashion to include healthcare facilities such as hospitalsand nursing homes and in addition to individual physicians or variousgeneral/specialized practice groups) by, in large part, tyingcompensation to adherence to the best practices standards and protocolsset by the local ACO or other responsible payor. In this fashion, and bydelegating responsibility for the formulation, administration andenforcement of the present system to the designated (e.g. local)payor/ACO, the various care providers are generally are understood toaccede to these established standards and protocols, thereby providingthe necessary participation for guaranteeing the success of the model.

The advantage of this system is that it rewards/compensates such careproviders based upon the desired outcome of treatment which is inaccordance with the established practices and protocols (quality oftreatment), and without regards to the quantum of treatment provided(number of tests ordered, surgical procedures performed, etc.). At thesame time, such care providers are rewarded for any level or quantity oftreatment (again including tests, procedures, etc.) which are consistentwith the desired standards established by the ACO and, equallyimportantly, are provided according to the protocols established. Oneapplication of this is to incentivize the care provider to follow thedesired practices and protocols first and before resorting immediatelyto invasive medical procedures which do not contribute to overallpatient quality of care so much as to the financial benefit of the careprovider. Beyond physician and physician groups, the present inventionsare further understood to apply to all clinical providers, not limitedto therapists, psychologists, nurses, and other healthcare facilitiessuch as nursing homes and hospitals.

A related module provides for optimizing the diagnosis, treatment andresolution of worker injury events, such as associated with a workmancompensation claim, and which improves upon the existing paper basedmodule by synthesizing, in a digital environment, symptom, treatment andprogress variables in a multi-party available format. In particular, theinjury event module greatly increases care provider (physician)efficiency by integrating and compiling electronically, in easilyreadable and time elapsed formats, symptom and treatment variables. Themodule additionally provides a reasonable and agreeable model, such asbetween the employer/payer and worker, for establishing minimal goalsfor facilitating return to work.

A further related rehabilitation module, such as not limited to a workerinjury event but also including any injury event associated with atypical accountable care organization (insurer/other payor/etc.) in ageneral health application is provided for establishing and tracking apatient's functional independent (FEM) measurement score. As with theworkman compensation module, the rehabilitation module integrates theestablishment of current conditions, achievable goals, and time basedtracking of the patient treatment (including time elapsed changes inresponse to flat line response indicating a non-effective treatmentplan) in order to define a patient goal outcome and to optimize realtime treatment and progress tracking to that goal.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the attached drawings, when read incombination with the following detailed description, wherein likereference numerals refer to like parts throughout the several views, andin which:

FIG. 1 is a schematic of an operational model according to onenon-limiting aspect of the present invention and which combines aspectsof shared savings agreements as applied to provisional of level of carealigned to evidence based best practice guidelines,

FIG. 2 is a related representation of a best practices algorithm dealingwith interactive events involving each of a primary care physician,physiatrist and surgeon;

FIG. 3 is a graph depicting Quality versus Spending and which identifiesa maximum point of return on investment;

FIG. 4 is a spreadsheet depiction of a care value index AHA (ACO)/SCspine program;

FIG. 5 is a flow diagram of the present system and which illustrates theinteractive nature of the central processor which interfaces with eachof the best brackets/incentive database, associated decision supportsystem, patient kiosk, provider scorecards and payor/ACO interface;

FIG. 6 is a first screen shot illustration of a best practices drivenscorecard which is derived from the present system and non-transitorycomputer writeable medium for providing a rating of the physician orother care provider on the basis of adherence to the practice objectivesand protocols established by the ACO or other designated authority;

FIG. 7 is a MODUS (loosely defined as an operational model for sharingrisks and rewards between healthcare payers, providers and patients)client spine spreadsheet illustration similar to FIG. 4 and whichprovides an exemplary breakdown of primary care physicians (PCP's) andassociated specialists (spine surgeon, chiropractor, psychologist,physical therapist, etc.) for a given client, such further illustratingsuch as best practices scores, overall percentage ratings, patientsatisfaction, payer cost and shared savings, the payments provided bythe ACO for the patient/client being bundled in a designated amount andthereafter distributed to the various providers as per the scorecardratings achieved;

FIG. 8 is an illustration of a patient enrollment screen display, suchas associated with the patient kiosk module, and which provides entryfields for enabling the patient to provide necessary information for thesystem, the incentive for entering can include specified rewards (e.g.gift certificates, etc.),

FIG. 9 is a screen illustration of an editable preferred specialtyproviders page associated with the scorecard aspects of the system andcomputer writeable medium and which provides detail as to particulartreatment options and protocols administered by that provider (such aswhich are condition specific in particular regards to spinal paintreatment) and along with corresponding best practice ratings;

FIG. 10 is a first colored (purple) flag screen illustration generatedaccording to the best practices protocol and associated decision supportsystem, resulting from an initial patient analysis and diagnosis, andwith a recommendation for treatment of a diagnosed impaired function ofthe patient by a primary care physician with specified (desired)options;

FIG. 11 is a succeeding illustration to FIG. 10 and depicting amanagement generated report based on the initial treatment decisions ofthe primary care physician,

FIG. 12 a second colored (yellow) flag screen illustration generatedaccording to the best practices protocol and associated decision supportsystem, resulting from an alternate initial or further patient analysisand diagnosis (to that provided in FIG. 10) and indicating an increasein the patient's anxiety level, and with a recommendation for treatmentof the patient by a primary care physician with additional specified(desired) options;

FIG. 13 is a succeeding illustration to FIG. 12 and depicting amanagement generated report based on the decisions of the primary carephysician;

FIG. 14 is a third colored (red) flag screen illustration generatedaccording to the best practices protocol and associated decision supportsystem, resulting from a succeeding and updated patient diagnosis tothat assessed in FIG. 10, and with a recommendation for a referral bythe primary care physician such as to a specialist;

FIG. 15 is a succeeding illustration to FIG. 12 and depicting amanagement generated report based on the decisions of the specialist;

FIG. 16 is a screen display of a comparison graph of a functional scorevs. group average for a given physician;

FIG. 17 is a management screen display and which provides complianceratings for care providers, based upon stages or gradations of careranging from in clinic care from the primary physician throughspecialist care and surgery;

FIG. 18 is a flow diagram of the predictive algorithm of the furthervariant of the non-transitory computer writeable medium of the presentinventions;

FIG. 19A is a first screen illustration of a patient informational entrypage associated with the variant of FIG. 18;

FIGS. 19B-1 and 19B-2 collectively depict a second screen illustrationof associated with the patient informational entry page and providing aseries of entry fields relative to such issues as stress, pain, etc.;

FIG. 19C is a third screen illustration associated with the patientinformational entry page and providing a series of entry fields relativeto establishing a patient functional level;

FIG. 20A succeeds FIG. 19 and provides a first screen illustration of aphysician (care provider) informational entry page;

FIG. 20B succeeds FIG. 20A and provides a second screen illustration ofa physician informational entry page and which includes additional entryfields with real time best practice compliance indication;

FIG. 21 is a counseling and feedback screen illustration regardingmanagement pathways established in FIG. 18;

FIG. 22 is a screen illustration of a dashboard page indicating realtime updated metrics including Best Practice Rate. Functional Score,Satisfaction and Cost, such further including ratings for each ofindividual score, group score and regional score;

FIG. 23 is a supervisor/employer information entry screen associatedwith a workman compensation module according to a further embodiment ofthe present inventions;

FIG. 24 is a succeeding supervisor/employer information entry screen tothat shown in FIG. 23;

FIG. 25 is a doctor assignment screen which the module produces inresponse to the inputs of the information entry screens of FIGS. 23-24;

FIG. 26 is a first confirmation of details screen outlining biographicalinformation to be entered by the worker/injured party;

FIG. 27 is a second confirmation of details screen providing additionalentry field for the worker/injured party to fill out includingconfirming details of the injury as reported by the supervisor, as wellas confirming and updating scope of duties;

FIG. 28 is a first symptoms input screen for the worker/injured party toindicate present physical symptoms/conditions;

FIGS. 29-30 is another view of the symptoms input screen of FIG. 28indicating symptom entry fields inputted by the worker relating to typeand intensity of pain;

FIGS. 31-39 illustrate a progression of symptoms catalog screens forweeks 1-9 from date of injury event and providing, for the viewingbenefit of all of the treating physician, the injured worker, and theACO/payor/employer condensed/synthesized and time elapsed progressmetrics displaying and tracking the injured worker's improvement incondition and function;

FIG. 40 a first worker ability input screen forming a portion of arelated sub-component of the workman compensation module and depicting anumber of entry fields which specify current ability metrics of theworker/patient;

FIG. 41 is a related worker ability screen which combines the currentability inputs of FIG. 40 with established goals;

FIGS. 42-44 are a progression of time charted ability screens whichtrack patient/injured worker current ability with goal ability over timeintervals, the objectives of which are to facilitate use by all partiesand in particular by the treating physician in the establishment and, ifnecessary, modification of the treatment protocol for obtaining fasterpatient recovery and achievement of (commonly agreed to) goals to enablereturn to work;

FIGS. 45A and 45B collectively depict a first rehabilitation settinginput screen according to a further module and providing a series ofpatient entry fields such as for each of prior function, currentfunction and goal function;

FIGS. 46-47 are rehabilitation setting screens depicting ranges incurrent, prior and goal function taken form the input screen of FIG. 45and for use in determining metric performance ranges between totalphysical assist and independent;

FIGS. 48A and 48B collectively depict a succeeding rehabilitation lengthof stay input screen contrasting current ability to goal ability andwith the objective of establishing determined goals for achieving amaximum possible level of patient independence for each of self care,sphincter control, transfers, locomotion, communication and socialcognition; and

FIGS. 49-51 present a series of overlapping and time elapsed treatmentand rehab length of stay screens which track the inter-ranges andadjustment/progress established between each of current function, goalfunction and prior function variables, with the objective being to closeor eliminate the ranges over a time variable extending from date ofadmission (compare date of injury as in workman comp module) and date ofdischarge (compare further to date of return to work in prior module).

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

With reference initially to FIGS. 1-4, a first non-limiting applicationof the present system, method and software/algorithmic based computermedium is depicted in the form of a specific spinal pain relatedapplication of the present invention, it being understood that, withsucceeding reference to FIG. 5 et seq., the present inventions areapplicable to any situation dealing with the providing of services, suchnot limited to any subset area of specialty involving the delivery ofhealthcare and can be equally applicable to non-medical related modelsin which the desire is to retrain/incentivize the various serviceproviders to focus on adherence to a best practices model andactual/verifiable patient/client outcomes, and as opposed to basing suchincentives and compensation on the quantity of service provided.

Referring again to the particular model of FIGS. 1-4, from a statisticalstandpoint, approximately 80% of the population will experience somelevel of spinal pain at some point in their lifetime. At any given time,31% of the population suffers from an existing spinal related issueSpinal fusion procedures currently account for the number 1 inpatientcost with spinal pain currently also the number 1 outpatient cost andsecond highest reason for work absenteeism. Other factors relating tothe costs of spinal pain and associated conditions include incidences ofemergency room visits (#3 for females and #5 for males for age groups15-65), the cost to the U.S. economy (presently $100 billion per year)and the percentage (41% to 87%) of worker compensation costs.

Existing spinal treatment protocols, such as in particular first orsecond level fusion of spinal vertebrae, further often result insignificant costs (surgical and hospital including for operating room,anesthesiologist, follow up care, etc.) as well as patient downtimeduring recovery. An outcome study in the state of Washington found 100%disability rate for patient undergone spinal fusion surgery. Othermedical conditions associated with persistent back pain, notably anxietyand depression, are a major factor in worsening the patient outcome andthe current care model fails to address the anxiety and depressionbecause the care for these conditions is not as lucrative as doingprocedures on these patients. In lieu of this, editable managementoptions are provided for various providers group preferences, along withcolor and numbers visual real-time feedback to users about theircompliance score (with subsequent reference to FIG. 17).

As a result of the fee for service payment system, providers arerewarded for doing more (procedures or medication prescriptions)regardless of the patient medical or functional outcomes. Currently, themedical system has very limited mechanisms to hold providers accountablefor their work and providers are often in fact rewarded for doing andproviding more care (and not necessarily better care) for theirpatients.

Existing treatment schemes (including fee for service models) rewardcare providers in volume as opposed to effectiveness of the care,resulting in significantly diminished returns on investment (asreferenced in the apex point depicted in the graph of FIG. 3), with evendecreased returns for significant additional investment as reflected inpatient morbidity and mortality. Providers compliance with best practiceguidelines for spine pain has always been low and in the study by Mafiet al 2013, the compliance with best practices it being noted asworsening over the past decade.

In response to the above conditions, the present system enables healthcare payers and to recognize value and pay for the provider's resultsinstead of just paying for efforts. Beyond that, the present inventionseeks to combine system, process and algorithmic based medium forestablishing a best practices protocol for treating a variety of medicalconditions (including spinal pain management). Referring first to FIG.1, a schematic of an operational model is provided according to onenon-limiting aspect of the present invention and which combines aspectsof shared savings agreements as applied to provisional of level of carealigned to evidence based best practice guidelines. The present systemwill measure data on clinical providers in regards to each of bestpractice compliance, patient's functional outcomes and patientsatisfaction. The unique data will further enable the payers to rewardproviders for their patients outcomes and not just for efforts (e.g.such as again measured in volume of service or care provided). Such asystem effectively makes the providers accountable to their patients andpayers.

FIG. 1 illustrates, at 10, an overall representation of a sharedservices agreement and which encompasses the interactive aspects of aCMS (Centers for Medicare/Medicaid Services) Private Payers Employers12, scientific consultants 14 and ACO (Accountable Care Organizations).By definition. ACO's are groups of doctors, hospitals and otherhealthcare providers that share responsibility for providing care fortheir patients. By coordinating their efforts, these groups providehigher-quality care in a more cost-efficient manner. They then share inthe profits from the savings that result. As further defined, anAccountable Care Organization can be developed through the Centers forMedicaid and Medicare (CMS) or privately outside of the CMS structure.

The shared services agreement (module) 10 interfaces with a furthermodule 18 encompassing a provisional of level of care aligned toevidence based best practice guidelines. A patient journey componentincludes designations for patients 20, primary care physicians 22 andspecialist care and other providers 24. A best practices algorithm (seeas generally represented at 26 in FIG. 1 and further delineated in FIG.2) is provided and interfaces the patient journey components withalgorithm adherence aspects including each of non-compliant care 28,medical director 30 and spine board 32.

Proceeding to FIG. 2, a related representation of the best practicesalgorithm 26 is provided and detail dealing with interactive eventsinvolving each of a primary care physician 34, physiatrist 36 andsurgeon 38 components. The patient journey starts with either theprimary care physician, a physiatrist or a spine surgeon and they allinitiate the care by checking, at step 1 (40), for any immediate redflags which are evidenced of serious pathological conditions (42) thenchecking for yellow flags associated with catastrophizing responses bythe patient who will need multi-disciplinary care term (that includespsychological care) and everyone checks for purple flags (documentingthe patient functional level) 36.

A magnetic resonance imaging (MRI) 44 step can succeed the evaluationstep 42, following which a surgical recommendation 46 of thephysiatrist. By definition, a physiatrist/rehabilitation physicians is amedical doctor who has completed training in the medical specialty ofphysical medicine and rehabilitation (PM&R). Specifically,rehabilitation physicians provide each of diagnosing and treatment ofpain, restoration of maximum function lost through injury, illness ordisabling conditions, treatment of the whole person, not just theproblem area, leading a team of medical professionals, providingnon-surgical treatments, and managing medical problems andtreatment/prevention plans.

By further definition, the job of a rehabilitation physician is to treatany disability resulting from disease or injury, from sore shoulders tospinal cord injuries. The focus is on the development of a comprehensiveprogram for putting the pieces of a person's life back together afterinjury or disease—without surgery unnecessary medical procedures and byincorporating the shared decision protocols integrated into the presentinventions.

Rehabilitation physicians are doctors of function, they take the timeneeded to accurately pinpoint the source of an ailment. They then designa treatment plan that can be carried out by the patients themselves orwith the help of the rehabilitation physician's medical team. Thismedical team might include other physicians and health professionals.These include such as psychologists, physical therapists, occupationaltherapists, health coaches, athletic trainers, social workers,neurologists, orthopedic surgeons, and physical therapists. By providingan appropriate treatment plan, rehabilitation physicians help patientsstay as active as possible at any age. Their broad medical expertiseallows them to treat disabling conditions throughout a person'slifetime.

Surgical recommendation 46 can result in yes 48 or no 50 steps. If yes,surgeon 38 module is activated and results in a surgical referral 51,progressing to an elective surgery medical director approval step 52,appeal of a spine board approval 54 and, finally, surgery 56.

Alternate to red flag step 40, a check for yellow flag step 58 proceedsto a determination if an Örebro score exceeds 80% (at step 60). The sameoccurs at previously identified step 50 in the instance of thephysiatrist (module 36) determining that surgery is not an option.

The Örebro Musculoskeletal Pain Questionnaire (ÖMPQ), formerly known asthe Acute Low Back Pain Screening Questionnaire (ALBPSQ), was developedto help identify patients at risk for developing persistent back painproblems and related disability.

The questionnaire is intended to be used with individuals who areexperiencing regional pain problems that are affecting their performanceat work, taking repeated short spells of sickness absence or arecurrently off work. In one version of the questionnaire, there aretwenty one scored questions concerning attitudes and beliefs, behaviourin response to pain, affect, perception of work and activities of dailyliving.

The questionnaire can usually be completed in 5 min before the patientmeets the health professional. A cut-off score of 105 and below has beenfound to predict, with 95% accuracy, those who will recover and, with81% accuracy, those who will have no further sick leave, in the next 6months.

Prediction of long-term sick leave (>30 days within the next 6 months)was found to be 67% accurate. A cut-off score of 130 and above correctlypredicted 86% of those who failed to return to work. The effect of thisscore is to assist the clinician to apply interventions (including theuse of activity programs based on cognitive behavioural strategies) toreduce the risk of long-term pain-related disability. Evidence indicatesthat these factors can be changed if they are addressed. It has alsobeen found that the total score is a relatively good predictor of futureabsenteeism due to sickness absence as well as function, but not ofpain. The results suggest that the instrument could be of value inisolating patients in need of early interventions and may promote theuse of appropriate interventions for patients with psychological riskfactors.

The primary care physician module 34 includes a further step 62 forchecking for the existence of a purple flag, this further indicating atstep 64 that the patient is likely disabled for two weeks or more (inturn leading to a similar purple flag analysis within physiatrist module36). Additional steps associated with the primary care physician module34 include each of step 66 for providing (to the patient) educationmaterial/videos relating to acute/chronic spinal pain, MRI or CT(computed tomography) procedures, surgery and associated injections, aswell as step 68 for providing treatment/therapy options (physicaltherapy, non-steroidal anti-inflammatory drugs or NSAIDS, Tramadol Rxshots, Acupuncture, chiropractic manipulation and yoga). Following thesesteps, and if worsening pain persists after six weeks with no yellowflags (step 70), an MRI procedure is performed at step 72 when advancingto the physiatrist module 36.

Physiatrist module also includes a similar step 74 (as compared to at 66in physician module 34). Step 76 recites additional treatment/therapyprotocols including up to three epidural procedures (see furtherfeedback loop interfacing with surgical module 38 and steps 52-54.Additional aspects of step 76 include each of use of multi-disciplinaryteams, psychology, bio-feedback and other aspects previously recited instep 68.

Additional aspects of the invention include the provision of a suitablesoftware component for effectuating some or all of the objects of theinvention, such including interfacing each of the modules 34, 36 and 38of the best practice algorithm, this in order to most effectively andefficiently providing for communication between the various careproviders and in order to enforce the objectives of the best practicesprotocol in order to avoid excessive treatments/procedures and, mostnotably, unnecessary surgeries in order to effectively treat many typesof spinal ailments. The software module is understood to interface withany suitable processor driven tablet, hand-held smart phone, laptop, PCor the like in order to quickly and efficiently interface each of themedical providers or other specialists described herein.

The care value index of FIG. 4, see at 75, provides one non-limitingexample of a tabular arrangement for providing a breakdown of individualmetrics for any plurality of care providers not limited to primary carephysicians (PCP's) and specialty care physicians such as spinalsurgeons, chiropractors, psychologists and the like. Referencing thetable of FIG. 4, the purpose for this is to provide one non-limitingexample of a series of metrics which can be used in establishing asupporting financial model for assisting in incorporating anexisting/most recently updated best practices protocol and in order todetermine both the maximum efficiency of investment referenced in FIG. 3(graph 75 depicting Quality versus Spending and which identifies amaximum point of return on investment), along with providing a readilyaccessible model for properly acknowledging and rewarding a provider forboth adhering to the best practices protocol. In concert with the abovedescription, the objects of the present invention include the ability topartner with providers networks in order to achieve better patientclinical and functional outcomes at lower cost. By rewarding providersfor integration, care coordination, adopting evidence based bestpractice and peer review, the present system results in minimizingunnecessary care which will result in benefits for patients,practitioners, employers, employees and third parties.

Proceeding to FIG. 5, a flow diagram is provided of the present systemand which illustrates the interactive nature of a central processor 78,which interfaces with each of a best brackets/incentive database 80, anassociated decision support system module 82, a patient kiosk 84, and aplurality of subset devices 86, 88, 90, et seq., associated with each ofa designated group of individuals or entities associate with a serviceprovider organization (such ranging from an individual physician to apractice group including classes of primary care physicians,specialists/surgeons, physical care specialists and the like). Alsodepicted at 92 is payor/ACO module which likewise interfaces with thecentral processor 78 and can include a separate computer, laptop or anyother processor driven device. The payor/ACO module is also generallydesignated as a management model and to account for the fact that thepayor/ACO may elect to designate an outside supervisory entity.

Without limitation, the processor 78 can include any type of computingdevice not limited to a hard drive containing computer, laptop, etc., aswell as a cloud based processor or database. The subset devices 86, 88,90 et seq. can further be provided as any of a laptop, tablet computer,smart phone or the like and which are in wired or wireless, including3G, 4G LTE, Bluetooth, or NFC (near field communication) with thecentral processor and its output functions.

As will also be now described with reference to FIG. 6 et seq., theimplementation and performance of the present system and method reliesupon the creation of an effective algorithmic based software programwhich is loaded into or otherwise interfaced with the central processor78 and its various communicating components 80-92. Such a softwareprogram can include various modules or components associated with eachof the hardware devices, in one instance a first software moduleassociated with the central processor module 78, as well as itsinterfacing lookup table incorporating the best practices model and theattendant decision support system, and which also includes additionalsubset modules in interfacing/two-way communication with the centralprocessor and module, such subset modules also envisioning being in theform of a mobile application which can be accessed by any of a laptop,tablet or smart phone.

Referring to FIG. 6 is a first screen shot illustration is provided at94 of a best practices driven scorecard which is derived from thepresent system and non-transitory computer writeable medium forproviding a rating of the physician or other care provider on the basisof adherence to the practice objectives and protocols established by theAC(O or other designated authority. Without limitation, this can includeproviding an ongoing rating (such as on a yearly basis) on a percentagebasis of an achieved best practices score (see for example at 57% at96), as well functional score (further example shown at 68% at 98) andservice score 100.

FIG. 7 is a spreadsheet illustration, at 102 and similar to as shown at75 in FIG. 4, and which provides an exemplary breakdown of primary carephysicians (PCP's on line item 6) and associated specialists (spinesurgeon on line 36, chiropractor on line 38, psychologist on line 40,physical therapist on line 42, etc.) for a given client, in thisinstance associated with a spinal treatment program. This illustrationfurther itemizes such as best practices scores, overall percentageratings, patient satisfaction, payer cost and shared savings, thepayments provided by the ACO for the patient/client being bundled in adesignated amount and thereafter distributed to the various providers asper the scorecard ratings achieved. The spreadsheet illustrations ofFIGS. 4 and 7 can generally represent one output and illustrativefunction associated with the management (ACO/payer) module 92 and whichassists in tracking the breakdown and distribution of lump sum budgetswhich are allocated to a given practice group/service provider.

FIG. 8 is an illustration, at 104, of a patient enrollment screendisplay, such as associated with the patient kiosk module, and whichprovides a series of biographical or other entry fields for enabling thepatient to provide necessary information for the system. The presentinventions contemplate the participation of the patient/client, not onlyin the inputting of information which is more efficiently obtaineddirectly as opposed to being recorded by other personnel, but also inthe ability to provide the patient/client with the ability to comment onthe performance of the care provider to further assist in assessing andscoring the performance metrics of that provider. The present inventionscontemplate providing incentives to the patient for his/herparticipation and such can include specified rewards (e.g. giftcertificates, discounts, etc.) for providing the requested information.

FIG. 9 is a screen illustration of an editable preferred specialtyproviders page, see generally at 106, associated with the scorecardaspects of the system and computer writeable medium and which providesdetail as to particular treatment options and protocols administered bythat provider (such as which are condition specific in particularregards to spinal pain treatment) and along with corresponding bestpractice ratings). As will be described with additional detail inreference to succeeding FIGS. 10-17, the specialty provider's page candesignate any one of a red 108, yellow 110 or purple 112 flag, as wellas providing a pain level indicator 114, a best practice compliancescore field 116, a functional field 118 and a service field 120.Additional designations 122-128 in FIG. 9 can reference color coding foreach of a succession of treatment option subsets, respectively at 2-5,and associated with various stages of spinal pain treatment.

FIG. 10 is a first colored (purple) flag screen illustration 139, suchas which can be associated with the management module 92, and which isgenerated according to the best practices protocol and associateddecision support system, and resulting from an initial patient analysisand diagnosis, and with a recommendation for treatment of a diagnosedimpaired function of the patient by a primary care physician withspecified (desired) options. Also depicted at 132 is a field designatingthat care provider's functional score in terms of best practicecompliance. FIG. 11 is a succeeding illustration to FIG. 10 anddepicting a management generated report 134 based on the initialtreatment decisions of the primary care physician and including entryfields for referrals 136, recommended educational videos 138, as well asrating identifiers (such as provided on a percentage basis) and againincluding best practice 140, functional score 142 and service score 144.

FIG. 12 a second colored (yellow) flag screen illustration 146 generatedaccording to the best practices protocol and associated decision supportsystem, this resulting from an alternate initial or further patientanalysis and diagnosis (to that provided in FIG. 10) and indicating anincrease in the patient's anxiety level (at field 148), and with arecommendation for treatment of the patient by a primary care physician(150) with additional specified (desired) options. FIG. 13 is asucceeding illustration to FIG. 12 and depicting a management generatedreport 152 based on the decisions of the primary care physician, alongwith and including entry fields for referrals 154, recommendededucational videos 156, as well as rating identifiers (such as providedon a percentage basis) and again including best practice 158, functionalscore 160 and service score 162. In application, this designation canfurther provide a final service outcome (the scorecard) that MODUS (asdefined herein) provides.

FIG. 14 is a third colored (red) flag screen illustration 164 generatedaccording to the best practices protocol and associated decision supportsystem, resulting from a succeeding and updated patient diagnosis tothat assessed in FIG. 10, and with a recommendation, at 166, for areferral by the primary care physician such as to a specialist. FIG. 15is a succeeding illustration to FIG. 12 and depicting a managementgenerated report 168 based on the decisions of the specialist, suchincluding a diagnosis field 170, referral field 172 and repeat ofcompliance ratings for best practice (not compliant as designated at174), functional score 176 and service score 178.

FIG. 16 is a screen display 180 of a comparison graph of a functionalscore vs. group average for a given physician and which assists intracking the real time performance of that individual relative to theoverall group. FIG. 17 is a management screen display and which providescompliance ratings for care providers, based upon stages or gradationsof care ranging from in clinic care from the primary physician throughspecialist care and surgery. The flag and rating fields 108-120described in FIG. 9 are repeated, along with additional fields 184-204,these respectively designating a scale of compliance ranging from 1(least intensive) to 11 (most intensive).

In application, the software/algorithmic based protocol can function inone instance to create a series of subroutines for operating the presentsystem and which include a first such subroutine for assembling a bestpractices model in the form of a database interfacing with the processordevice and which presents series of treatment options ranging fromdesirable to undesirable associated with a given type of service. Asecond subroutine provides a decision support system interfacing withthe best practices database and processor device, the support systemproviding any of a grading or awarding system for scoring, in real time,performance metrics for each of any number of providers of the service.

A third subroutine outputs to a plurality of subset processor devicesassigned to each of the providers, real time and continuously updatedscoring of their performance metrics based upon the grading/awardingsystem and as a result of the treatment options selected and inputted bythe provider. A fourth subroutine (such as which can be integrated intothe third subroutine) incentivizes adherence by the providers to thebest practices model by tying desirable performance metrics to financialincentives which are scaled to each treatment option.

Additional subroutines include providing and incentivizing patient inputto the processor driven device in the form of at least one ofmedical/biographical data input and commentary/rating regarding theservice provider. A management module can also include at least oneadditional subroutine interfacing with the processor driven device formonitoring and tracking adherence to the best practices model.

Additional subroutines can designate a sum of funds representative of anoperating budget for the service provider and for disbursement on apercentage basis to each of any number of subset service providers basedupon adherence to the best practices model. This can further includesubdividing the sum between different practice groups andsub-specialties associated with a given class of service providers.

Addressing the initial example described in FIGS. 1-4, one subsetapplication of the software based algorithmic medium can in particularinclude the treatment options associated with said first subroutinefurther including being integrated into a medical care protocol andfurther including any one or more of a first physician service providerassessing a patient's condition, a second physiatrist service providerfurther assessing the patient and interfacing with said first physicianin an extreme diagnostic event, and a third surgeon service provider foradditionally assessing the patient and interfacing with the secondphysiatrist service provider in at least an epidural related event. Thiscan further include an MRI procedure associated with an interfacingevent between the physician and physiatrist modules.

FIG. 18 is a flow diagram of the predictive algorithm of the furthervariant of the non-transitory computer writeable medium of the presentinventions. As previously described, this variant of the non-transitorycomputer writeable medium incorporates a predictive algorithm whichincludes a series of protocols for modifying a base or template versionof the algorithm into any of a number of modifications or sub-variantsand in order to quickly and conveniently customize the computerwriteable medium.

A first protocol 206 or subroutine for establishing a risk profilethrough stratifying a designated ACO population. For purposes ofdefinition, the ACO population constitute a membership of a health careplan or other designated group of individuals for which medical coverageis provided and further for which a designated sum of funds is depositedor otherwise retained for providing payment for services rendered onbehalf of the membership or target group.

A second protocol or subroutine, see at 208, of the predictive algorithmfurther operates by training the ACO doctors or other care providers inone or more of a series of medical related diagnosis and treatmentprograms (or disciplines) these further potentially including but notlimited to any one or more of joint care 210, spine care 212, cardiaccare 214, acute care 216, post-acute care 218, wound care 220, vascularcare 222, cancer care 224, diabetes care 226, kidney care 228, urologycare 230, pulmonary care 232 and vision care 234. In one non-limitingvariant, a base algorithm is provided which includes a pre-programmedsubroutine program or code directed to any one or more of the above caredisciplines 210-234, it being further understood that the listingprovided is open-ended and can be augmented or substituted by any othercare specialty or sub-specialty for which an ACO can provided coverage.

A third successive protocol/subroutine includes establishing one or moremanagement pathways which are customizable by the ACO leadership, see asdesignated at 236. By way of explanation, the customization orconfiguration of the predictive algorithm is facilitated by a series ofquestions and answers which are built into the customization aspects ofthe software and which are asked of the care providers assigned to oneor more of the enumerated specialties.

In this fashion, the questioning protocol built into the pathwaysbetween the second 208 and third 236 subroutines provides for thenecessary modification/customization of the base algorithm, such as forany one or more of a variety of treatment sub-species, and in order toestablish subroutines at this stage for any one or more of emergencycare 238, immediate care 240, systemic complications 242, disabilityrisk 244, psycho-social issues 246, preventive care 248 and/ormaintenance care 250. As previously noted, the lists provided herein areopen ended and can be substituted or supplemented by additional caresubspecies without departing from the scope of the inventions describedherein.

A fourth protocol/subroutine 252 provides care provider (e.g. doctor)feedback on the desired best practices for the given diagnosis andtreatment sub-species resulting from the question and answer protocolachieved in the third subroutine. As with the previous disclosedembodiments, this can include providing any type of grading or codingprotocols, such as utilizing and combination of letters, colors or othergenerally identifiable symbols for conveying visualization of thegrading of the specific care providers conduct as reflective of thepre-established best standards which are integrated into the algorithmicfunctions of the associated program.

A fifth protocol 254 results in the creation (again by the ACO or otherprovider) of a scorecard for each individual care provider (doctor,therapist, etc.), such based primarily upon patient outcome assessmentand accounting for patient complexities. Such informational feedback, aspreviously described, can be communicated via electronic device (seehandheld tablet as depicted at 256). In this fashion, shared savingsresulting from the implementation of the program results are distributedbased on the simplicity, transparency and accountability provided by thepresent system and computer writeable medium.

Proceeding to FIG. 19A, a screen illustration is generally shown at 258of a patient information entry screen associated with the variant ofFIG. 18 and which illustrates a series of fields which can be selectedchecked by the patient. These include individual Yes (check mark), No(X) or question (?) fields for selected symptoms including each of NightSweat 260, Fever or Chills 262, History of Cancer 264, Recent Infection266, Recent Trauma 268, Impaired Balance 270, Poor Coordination 272,Tripping or Falling 274, Loss or Changed Sensation 276, Numbness orTingling Sensation 278, Localized Weakness 280, Paralysis 282, Neck Pain284, Back Pain 286, Joint or Limb Pain, Stiffness 290, Limited Range ofMotion 292, Swelling 294, Headaches 296, Anxiety or Depression 298,Stress of any Kind 300, Disturbed Sleep 302, Unintentional Weight Loss304, Blood in Urine 306, Blood in Stool 308, Bladder or Bowel Problems310, Abdominal Pain 312, and Other Symptoms 314.

A check mark (Yes) for any of these symptom fields further brings up a“Tell us More” data key entry field which allows the patient user toprovide additional information. A similar field is brought up in theinstance of the right side (?) icon being selected for entry ofadditional patient provided information. Other features include a StartOver button 316 and a Next button 318. The screen display 258 mayfurther include a patient identity field 320 and a care disciplineidentifier 322 (see also Spine field 212 in FIG. 18).

FIG. 19B is a second screen illustration (divided into FIGS. 19B-1 and19B-2) of associated with the patient informational entry page andproviding a series of entry fields relative to such issues stress, pain,lost productivity, etc. Referencing FIG. 19B-1 initially, this includesentry fields for indicating pain in any one or more of arm 324, leg 326,lower back 328, neck 330, shoulder 332 or other 334. Also indicated arefields for days of work missed 336, duration of current pain 338 andlast day of work 340.

An additional series of patient entry fields are provided for physicalaspect of work 342, pain rating over previous week 344, average scale ofpain over past 3 months 346, severity and frequency of pain episodesover past three months 346 and 348, and pain decrease success 350.Corresponding scale selections are provided for each of the additionalentry fields 342-350.

FIG. 19B-2 also includes fields for each of tension over previous week352, depression over previous week 354, current pain persistence risk356, probably of working in 6 months 358, job satisfaction with currentlimitations 360, physical activity to pain correlation 362 andconsequent rescission of work function 364, and cessation of normal workat current pain level 366. As with FIG. 19B, corresponding scaleselections are provided for each of the additional entry fields 352-366.

Also depicted in FIG. 19B-2 are a selection of five activities, thepatient entry answers to which are scaled from 0-10 and include each of“I can do light work for an hour 368”, “I can walk for an hour 370”, “Ican do ordinary household chores 372”, “I can do the weekly shopping374” and “I can sleep at night 376”. Previous 375 and Next 377 fieldsare located at the bottom of the page to facilitate either going back toscreen page 19B-1 or forward to 19C.

FIG. 19C is a third screen illustration associated with the patientinformational entry page of FIG. 19 and providing a series of entryfields relative to establishing a patient functional level. Thisincludes a pain score bar 378 with an adjustable range between no painand worst pain ever for each of Pain Intensity 380, Personal Care 382,Lifting 384, Walking 386, Sitting 388, Standing 390, Sleeping 392, SexLife 394, Social Life 396, and Traveling 398. Also illustrated areprevious 400 and submit questionnaire 402 fields.

FIG. 20A succeeds FIG. 19A-19C and provides a series of Review ofSystem/Physician Clinical Decision informational entry page 404, suchrepeating the patient identity field 320 and care discipline identifier322 from FIG. 18. This includes Positive Responses (field 406)designations for each of Loss or Changed Sensation 408, Numbness orTingling Sensation 410 and Back pain 412.

FIG. 20A provides additional fields including “?Unsure” 414, indicatinga sub-field for Bladder or Bowel Problems 416, as well as a Negativeresponse field 418 indicating such as Night Sweat 420, Fever or Chills422, History of Cancer 424, et seq. Other fields include Pertinent HPIand Other History 426, Pertinent Physical Examination Fields 428 and 430and Medical Decision Making Field 432 including a variety of individualconditions 434 (including each of Infection, Fracture, Cancer, CaudaEquina, Pending Paralysis, Weakness, Radiculopathy, AnkylosingSpondylitis). An alternate “None, Continue” field 436.

FIG. 20B provides a further screen illustration succeeding FIG. 20A forthe care provider informational page and including g a series ofinformational entry fields along with real time displays for CurrentPain 438, Function 440, Satisfaction 442 and Best Practice Compliance444. Also provided are a series of provider entry fields for determininga treatment level for a selected disability or psychosocial malady. Thisincludes counseling 446 such as for each of back pain 448, hip & kneesurgery 450, stress 452, exercise 454, activity 456 and opiates,medication 458.

FIG. 20B also provides a series of physician/care provider entryselections for given treatment protocols, such corresponding to the realtime tool bar functions 438-444. These include any one or more of PMRConsult or Psychology 460 (at scale of 100), Exercise and/or PMR Consult462 (scale 90), Physical therapy (PT) session 464 (scale 80), one ormore of NSAID, Tylenol, Benzos or Rest options 466 (at scale 70),Tramadol 468 (scale 50), magnetic resonance imaging (MRI) or computedtomography (CT) 470 (scale 40), Norco 472 (scale 30), Epiduralinjections 747 (scale 20) and Spinal Surgery Consultation 476 (scale10). Confirm management selection 478 progresses to the last screen,FIG. 21, described as follows.

FIG. 21 is a counseling and feedback screen illustration 480 regardingthe management pathways established in FIG. 18. Again repeated is thepatient identity field 320 and care discipline identifier 322 from FIG.18. Also repeated are the Current Pain 438, Function 440, Satisfaction442 and Best Practice Compliance 444 fields from FIG. 20B.

FIG. 21 provides for physician counseling for patients, as well asinstant (real time) feedback on management choices determined in theflow diagram of FIG. 18 (between steps 308 and 236 as described above).As previously explained, the pathway and options for management changesdepend on the patient informational input, as well as the physician'sanswers to the questions posed between the steps in the FIG. 18 flowdiagram.

An Emergency Care section 446 includes a Counseling field 448 which iscustomized to indicate which sub-fields taken from Back Pain, Hip & KneeSurgery, Stress, Exercise, Activity and Opiates medications have beenchecked. The feedback aspects of the Management page 480 furtherprovides scaled selections 100, 90, 80, 70, 50, 40, 30, 20 and 10. Adesignation (check) of one of these boxes corresponds to each of StatMRI/CT (for one hundred at 450), Stat Neurosurgery Consult (for ninetyat 452), Direct Hospital Admission (for eighty at 454), ER (for seventyat 456), PMR Consultation (for fifty 458), NSAIDS (for forty 460),Opiates (for thirty 462), Benzos (for twenty 464) and PT or physicaltherapy for the lowest percentage or scale (for ten at 466). Alsoindicated is a confirm management screen 468 for designatingconfirmation of review by the Payor/ACO.

Finally, FIG. 22 is a screen illustration of a dashboard page 470indicating real time updated metrics for each of Best Practice Rate 472,Functional Score 474, Satisfaction 476 and Cost 478 (in each instancefor selected year 2014). Aspects of this page may also includeidentification of given car provider 480 for which scoring is provided.

Each of Best Practice Rate, Functional Score, Satisfaction and Cost mayfurther be further subdivided to provide breakout ratings or scores foreach of individual/group/region, as further shown at 482, 484, 486 and488 respectively, such again in ratings of 0-100. Also shown is a Filterby Chief Complaint Field 490, such including further selectable fieldsincluding each of spine 492 and joint 494. Alert field 496 also providesfor providing additional feedback and communication between the payor(ACO) and the care provider.

Given the above description, the present invention (including each andall of the system, method and non-transitory computer writeable medium)accordingly provides an incentive structure for rewarding care providersbased upon best practice decision making (quality or outcome dependent)and not merely upon quantity of services provided (e.g. tests ordered,surgical procedures conducted etc.). In this manner, health care dollarsare more equitably distributed as well as saved by such a merit/outcomebased sharing and distribution scheme, such that the service careprovider (physician or other like) can also be paid a bonus as anincentive for keeping their patients/clients more healthy, more able(less disabled) ad more satisfied, as well as preventing theadministration of unnecessary treatments and procedures such as areattendant with current quantity of service based compensation models.

Variants of the present system also contemplate a pool or bundle offunds being designated (such representative of historical costs incurredfor any given number of physicians or practice groups, including tiersof care providers drawn from PMP (primary care physicians), specialists(cardiology, spinal surgery, etc.), these being paid out on a percentagebasis to the various care providers based upon their individualscorecard results regarding adherence to the best practice protocolsestablished by the relevant ACO/care provider, such further reflectingthe results/outcome of the treatment provided (i.e., outcome drivenperformance by the physician or other care provider based results andnot compensated as a variable of the quantity of, often unnecessary,services).

Additional advantages include the establishing of performance metricsfor clinical providers that are based on adherence to best practice,patient's functional outcome, patient satisfaction and cost. Adherenceto the model created in the present invention further derives from theauthority implicit in the local ACO or other payer and, along with thecreation of transparent metrics for achieving higher compensationlevels, serves to more equitably distribute shared savings and otherfinancial incentives between all of the various stake holders (patients,care providers, and payers).

Other advantages of the system include the ability to readily monitorand record the providers/physician's choices in a real-time decisiontree which interfaces with the decision support system module and whichis reflected in the continually updated scorecard for each suchphysician/provider. In this fashion, real time feedback to the physicianis achieved to monitor ongoing activity in regards to the diagnosis andtreatment provided, with the incentive driven compensation structure inplace for guiding and influencing such decision making in the directionsdictated by the ACO/payer.

In this fashion, the present system, method and computer writeablemedium provides a tools to the management portion of the operation ormodel (e.g. payers, provider organizations, ACO's, etc.) for carryingout the management of the provider's preferences and behavior (as againdictated by the formulated best practices protocols), such furtherenabling the management portion to control utilization and expenditureof the resources allocated to such care.

In this fashion, customization of the present system is made possible ofthe best practices formulated, such by the responsible payer or ACO forvarious types of disease management based upon the manager's(payer's/provider organizations/ACO) preference) and which can furtherbe modified for any criteria or input not limited to differences ingeography (i.e. best practices may vary from locale to locale and thepresent system builds in the flexibility to take this into account). Thereal-time performance metrics achieved by the present system also enableinstant feedback to the providers to both assess current practice and toprovide direction (along with accompanying incentives) for adhering tothe formulated best practice protocols for present and future treatmentof the patient.

The report card aspects also provide comparison metrics for each of theproviders/physicians, this further providing a competitive environment(not driven exclusively by dollars) for adopting and adhering to thebest practice protocols formulated by the management portion (e.g.including or representing the interests of the payer). The rewardmechanism of the present invention is also modified and calibrated tocover any type of care provider (or groups of care providers) notlimited to primary care physicians, specialists, or combination/groupsof such providers which may be incorporated into a given practice orother entity.

The additional advantage of providing a reward mechanism forparticipation of the patient (not limited to providing coupons orrebates for undertaking data entry functions), further assists inmaximizing the efficiency and economy of the medical records componentof the system, as well as assisting in the formulation of correct andunbiased scorecard evaluations of each provider/physician by integratingthe patient experience and input into the incentives driving the system.

Summarizing, a listing of the objective made possible by the presentinventions include, but are not limited to, each of the following:

1. Establishing an algorithmic computerized medical providers scorecard.

2. Providing an algorithmic computerized operational tool to promoteproviders collaborations, coordination, integration and shared decisionmaking.

3. Establishing an algorithmic computerized operational method forbundle payment management.

4. Creating an algorithmic computerized operational model for paying forperformance.

5. Using an algorithmic computerized reward/incentive system toencourage providers to follow of best practice.

6. Establishing algorithmic computerized performance metrics forclinical providers that are based on adherence to best practice,patient's functional outcome, patient's satisfaction and cost.

7. Creating an algorithmic computerized transparent operational modelfor the distribution of shared savings and other financial incentivesbetween all stakeholders (patients, providers and payers.

8. Algorithmic computerized system for monitoring and recording ofproviders choices in a decision tree.

9. Provide real time, instant algorithmic computerized feedback forproviders compliance with best practice on every patient enrolled in theprogram.

10. Providing an algorithmic computerized tool to managers (payers,providers organizations/ACOs) for management of providers preference andbehavior and enables the management of providers groups to controlutilization.

11. Customizable algorithmic computerized best practice options fordisease management based on the managers (the payers/providersorganizations/ACO) preference (given best practice can varygeographically).

12. Providing algorithmic computerized real time, instant feedback forproviders for overall year to date compliance for their patientpopulation.

13. Providing an algorithmic computerized comparison metric forproviders to measure their performance vs others in the group and othergroups.

14. Enabling the managers (the payers/providers organizations/ACO) touse algorithmic computerized to create and manage an editable specialtyphysicians providers network.

15. Use algorithmic computerized System for empowering patients andproviders teams by linking the individual provider financial incentivesto the patient's and team's experience.

16. Creating an algorithmic computerized system to use as a rewardmechanism for patients' compliance with care and electronic data entryinto the providers medical records system.

To summarize, and drawing on the above disclosure, the predictivealgorithm of the present invention (MODUS) provides for riskstratification of the population and, based on the results extracted,(co-morbidity's, Socioeconomic, psychosocial and other risk factors),the Modus predictive algorithm provides clinical management pathways,that are customizable by the ACO's (the providers group) leadership orthe healthcare payer (insurance carriers of self insured employer).

The pathways are meant to:

-   -   a. Be a check list reminder process about best practice on        routine/common clinical conditions (to help providers remember        the mundane “stupid” items, that can cause significant problems        if they are missed.    -   b. Preventive care reminders for various propulsion needs.    -   c. Standardize care based on beast practices guidelines    -   d. Inform providers at all levels (PCP, specialists and others)        of the ACOs expectation for managing their population with        various clinical conditions and co-morbidity's (Doctors will        feel confident and less anxious about making care decisions that        are researched, informed and recommended by their ACO)

Pathways starts with a basic low risk and complexities (Maintenancecare), and built up as risks and complexities increases in a patient(Emergency care, immediate care, Systemic complications, Disabilityrisk, Psycho-social and preventive care)

Pathways will increase flexibility for the ACO to focus time andresources allocations on the highest risk patients.

Additional envisioned embodiments include applying the system, methodand associated algorithmic based (software) medium to other medical and,potentially, non-medical applications beyond those described herein,such as including but not limited to orthopedics conditions, diabetescare, cardio-pulmonary related chronic conditions, cancer and the like.

Depending further on the chronic condition we are managing, the presentsystem and model will be adjusted accordingly and appropriate clinicalproviders will be deployed for it and outcome measures will be adjustedto be relevant to the chronic condition. Subject to modification, theproviders will generally be PCPs (primary care physicians), then anon-interventional specialist and an interventional specialist. Forexample in cardiac care the team will include PCPs, cardiologists andinterventional cardiologist and cardiac surgeons (along with teams ofdietitians, physical therapist, exercise physiologists, trainers) aswell as relevant educational material that will be provided to thepatients.

Given the above discussion of the modules covering the rating system,process and medium for establishing best practices compliance tied tocompensation (FIGS. 1-17) and for establishing an optimizing apredictive algorithm for treatment of patient conditions (FIGS. 18-22),the present inventions additionally disclose a pair of related modulescovering both workman compensation (FIGS. 23-44) and general ACO/insurerrehabilitation (FIGS. 45-51) variants. In each case, the workman compand rehab modules are configured utilizing many similar components asassociated with the previous variants and provide for optimizing thediagnosis, treatment and resolution of either of worker or generalpatient injury events.

As will be further described, and in associated with a workmancompensation claim, the module improves upon the existing paper basedmodel for documenting and processing such claims, this by synthesizing,in a digital environment, all of symptom, treatment and progressvariables in a multi-party available format. In particular, the injuryevent module greatly increases care provider (physician) efficiency byintegrating and compiling electronically, in easily readable and timeelapsed formats, symptom and treatment variables. The moduleadditionally provides a reasonable and agreeable model, such as betweenthe employer/payer and worker, for establishing minimal goals forfacilitating return to work.

Prior employing the workman compensation module, the employer/payer(also ACO as previously defined) will choose a providers network, e.g. agroup of medical professionals and ancillary support staff includingpersonal therapists, pharmaceutical staff, imaging specialists,hospitals, and the like. As per the initial module of FIGS. 1-18, a bestpractices model is established with corresponding payment and feeschedules and, as further depicted in succeeding FIGS. 19-22, predictivealgorithms are integrated for establishing specific recommendedtreatment protocols.

At this point, and referring initially to FIG. 23 a supervisor/employerinformation entry screen 500 is provided (such as again integrated intoa processor based device) which, following the occurrence of a workerinjury event, constitutes the initial action in the opening andreporting of the event. A series of entry fields include each ofSupervisor Name 502, Company 504, Position 506, Email 508, Phone 510,Address fields 512 and 514, City 516, State 518, Zip Code 520 andContinue button 522.

FIG. 24 is a succeeding supervisor/employer information entry screen, at524, to that shown in FIG. 23 for inputting injured worker details andincluding fields for each of Worker Name 526, Date of Birth 528, Email530, Phone 532, Address fields 534 and 536, City 538, State 540, ZipCode 542, Injury Details 544, Description of Injury field 546, InjuryDate 548, Injury Time 550 and concluding with Job Duties 552 for thesupervisor/employer to list the routine job duties of the worker.Following clicking submit button 554, and proceeding to FIG. 25, adoctor assignment screen 556 is provided which the module produces inresponse to the inputs of the information entry screens of FIGS. 23-24for assigning a doctor of suitable qualifications and training (i.e.trained in physical medicine and rehabilitation or PMR, occupationalmedicine, sports medicine, etc.) for treating the injured worker.

For convenience, the doctor assignment screen further includes addressand map information and, as will be described throughout the succeedingscreens of the workman comp module, the physician/doctor's role at thispoint is to establish a patient/physician relationship (i.e. to functionas the primary care physician and to examine and treat the worker'sinjury). As will be further described, the doctor further functions toassist in setting up realistic and achievable goals for recovery offunction of the patient/worker over a given time frame, the objectivebeing to facilitate return to work once minimal and commonly agreed tometrics (as between physician/payor/worker) are achieved.

Following clicking on continue button 558, a Confirmation of Detailspage 560 at FIG. 26 is accessed in which a number of personal fields arelisted, including biographical fields for each of Patient Name 562, Dateof Birth 564, Last Four Digits of Social Security 566, Email address568, Phone Number 570, Address fields 572/574, City 576, State 578, ZipCode 580, Emergency Contact fields for Name 582, Relationship 584 andContact Number 586, and finally Family Doctor (regular PCP) Name 588 andContact Number 590. For purposes of security, Password 592 and RetypePassword 594 fields are also provided and, once completed Continuebutton 596 is accessed to advance to Confirm Injury Details screendisplay 598 of FIG. 27.

FIG. 27, based on the information previously inputted, provides anexplanatory (non-editable) field for Injury as described by yoursupervisor 600 as well as a worker input field 602 for insertingadditional injury details. Also listed are a series of duty fields aspreviously recorded by the supervisor for review by the worker forpurposes of assessing accuracy, this intended to provide an exemplaryand non-limiting summary of the typical performance metrics which theworker is expected to achieve.

By example, FIG. 27 provides such a non-limiting summary as includingperformance metrics for “Lifting 20 lb every 1 hour” (600), “Driving ahilo 3 hours a day” (602), “Picking material off 3 hours a day” (604),“Cleaning containers” (606), “Rolling Sheets” (608), “Typing on aComputer” (610), “Walking between work stations” (612), “Managinginventory” (614), “Calling on staff members” (616), “Answering phonecalls” (618), “10 hours/day” (620), and “4 days a week” (622). In thismanner, FIG. 27 also provides additional entry fields for theworker/injured party to fill out including confirming details of theinjury as reported by the supervisor, as well as confirming and updatingthe scope of duties as provided, following which submit button 624 isaccessed to advance to the patient treatment portion of the module.

Proceeding now to FIG. 28, a first symptoms input screen 626 is providedfor the worker/injured party to indicate present physicalsymptoms/conditions relating to the treatment stage. As with each of thesucceeding screen displays through FIG. 39, a pair front 628 and back630 pictorial representations are provided of a patient and in which thepatient (either alone or in the presence of the participating physician)can indicate a physiological location (see inner right elbow 632 inrepresentation 628). Additional fields are provided for indicating painintensity (at 634) with an associated 1-10 pain scale (at 636).

A further field 638 is provided for indicating type of pain (seeselecting fields for Aching 640, Stabbing 642, Burning 644 andNumbness/Tingling 646). Comment field 648 is also provided and includesentry location for comments (at 650) such as when pain started, whatcaused it, what makes it better or worse, other symptoms, etc. Alsoprovided is an add symptoms area 652 and, in combination with listfields for Location 654, Type 656, Intensity 658 and Other Symptoms 660,facilitate listing of the additional symptoms. FIGS. 29-30 are generalrepeats of the symptoms input screen of FIG. 28, at 662 and 664,respectively, with pain intensity level 636′ (at 6) indicated in FIG. 29and aching pain 640 designation provided in FIG. 30.

Proceeding to FIGS. 31-39, illustrated are a progression of symptomscatalog screens for weeks 1-9 from date of injury event and providing,for the viewing benefit of all of the treating physician, the injuredworker, and the ACO/payor/employer condensed/synthesized and timeelapsed progress metrics displaying and tracking the injured worker'simprovement in condition and function. Referring first to FIG. 31, ascreen illustration 666 is provided again showing the front 628 and back630 pictorial representations, the back illustration further includingpain indications 640, 644, 646 et seq. which can be entered by eitherpoint and click and/or by capacitive touch (tactile) interface.

Pain Record entry fields are further provided for each of Neck 672,Shoulder 674, Arm 676, Forearm 678, Hand 680 and Head 681, eachdepicting a selected variety of pain fields again including each ofAching 640, Burning 644 and Numbness/Tingling 646. Pain Intensityindicator 682 provides a range (typically between 1-10) for each of theafore-mentioned areas of pain, with Comments field 684 provided forlisting any related patient conditions.

FIG. 32 provides a succeeding screen illustration 686 of a SymptomsCatalog for a further time interval shown at 688 as corresponding toweek 2 from an injury event. Further succeeding screen illustrations areshown at 690 for week three 692 (FIG. 33), at 694 for week four 696(FIG. 34), at 698 for week five 700 (FIG. 35), at 702 for week six 704(FIG. 36), at 706 for week seven 708 (FIG. 37), at 710 for week eight712 (FIG. 38) and, finally, at 714 at week nine 716 (FIG. 39). Asfurther shown, the pain intensity variables are shown decreasing fromweek to week (FIGS. 31-39) for pictorial depictions 628 and 630 andassociated intensity readings 682.

The Pain Record, Intensity and corresponding pictorial representationsas shown also decrease in both quantity and intensity over the course ofFIGS. 31-39 (week one to week nine) corresponding to the improvement ofthe worker/patient and such that, by week nine, only minor neck pain 672remains with numbness 646 at pain intensity level two. In this fashion,the module provides a condensed and synthesized record of past andcurrent patient metrics (pain type, level, etc.) which enable thephysician to optimize present and future treatment protocols (theseagain consistent with the previous best practice module (FIGS. 1-17) andpredictive algorithm module (FIGS. 18-22) to ensure that the correct andoptimal treatments are applied to the injured worker/patient in order toexpedite patient recovery.

Proceeding to FIG. 40 a first worker ability input screen 718 is shownforming a portion of a related sub-component of the workman compensationmodule and depicting a number of entry fields which specify currentability metrics of the worker/patient. These include patient inputted(or supplied) current ability for a non-limiting listing of duties, suchas particular to the expected abilities of a given job description andincluding each of “A. Lifting 20 lb every 1 hour” (at 720), “B. Drivinga hilo 3 hours a day” (at 722), “C. Picking material off 3 hours a day”(at 724), and “D. Cleaning containers” at (726).

As further shown, the ability ranges can include any given percentagebreakdowns, such as shown including effort percentages which theworker/patient needs to expend in order to accomplish each of theenumerated duties for each of 1-25% (at 728 for Minimum Effort), 26-50%(at 730 for Moderate Effort), 51-75% (at 732 for Severe Effort), 76-100%(at 734 for Extreme Effort) and, finally, >100% (at 736 for PhysicallyUnable). As further shown, a score column (at 738) is provided fortallying grades of between one to five for each duty (e.g. as shownminimum effort corresponding to a score of five, moderate a score offour, severe a score of three, extreme a score of two, etc.). An averagegrade (see 3.5 at 740) is indicated for providing a Current Ability ofthe injured worker patient (as further determined by a date 742indicated at the top of the screen). Finally, submit button 744 providesfor entering of the data screen information and advancement to the nextscreen (FIG. 41 as described).

FIG. 41 is a related worker ability screen, at 746, which combines thecurrent ability inputs of FIG. 40 with established goals (defined asgoal ability 748) constituting a reachable performance ratio discussedbetween the physician and patient and which may also represent anintermediate or final metric which needs to be achieved in order for theworker to be cleared to return to partial/limited or full duties. Thisdiscrepancy (or difference) between the current ability 740 and goalability 748 is further indicated as an ability gap (at 750) and submitbutton 752 enters the information of screen FIG. 41 prior to advancingto subsequent FIGS. 22-24.

Referencing now each of FIGS. 42-44, a progression of time chartedability screens are provided which track patient/injured worker currentability with goal ability over specified time intervals (such as isshown on a weekly basis), the objectives of which are to facilitate useby all parties and in particular by the treating physician in theestablishment and, if necessary, modification of the treatment protocolfor obtaining faster patient recovery and achievement of (commonlyagreed to) goals to enable return to work FIG. 42 (ability screen 754)establishes a range on a weekly or other time interval established basisfor each of goal ability 756 and current ability 758 for each of thepreviously identified duties 720, 722, 724, et seq.

As such, FIG. 42 compiles and presents, for the benefit of physician byoptimizing the efficiency and minimizing the time investment in thetreatment of the injured worker, data points for each of theafore-mentioned duties in the form of graphical ranges between currentability and goal covering a given succeeding time intervals (see gap 4.5for week one at 760, gap 4.5 week two at 762, gap 3.1 for week three at764, gap 2.7 for week five at 766, gap 1.5 for week eight at 768 and,finally gap 0 for week nine at 770). Drop down menus for selecting range(plus or minus for 772) and duties (further at 774) are also provided.As further shown, the ranges between current ability and goal ability,and corresponding gap, decrease from the first recordation (again weekone at 760) following the injury event to the final recorded event (weeknine at 770), such corresponding to an achieved metric which has beenpreviously agreed to between the employer/supervisor and the worker aspart of a workman compensation negotiation for facilitating a return towork event.

Succeeding screen 776 for FIG. 43 substantially repeats the informationfrom screen 754 of FIG. 42, with the duties menu 774 selected toindicate such as those duties previously identified at 720, 722, 724, etseq., and referenced as A-L. The current and goal ability metrics arefurther presented in both light (current 758) and dark (goal 756)shading in the corresponding range depictions in order to provide aquick graphical interface to indicate a progression of the shrinking orminimizing of the degree of range or gap between current and goalabilities week to week until the gap is minimized or eliminated.

FIG. 44 provides a yet further representation at 778 of a graphicalprogression (see generally at 780) which is assembled by the presentmodule algorithms and which is intended to represent an overallprogression of current ability over time. As shown, the graph 780includes a first linear component 782 representing weeks 1-3 which cancorrespond to initial post injury time intervals in which the treatmentsprescribed by the physician are not effective in the treatment of theinjured worker/patient.

As further shown, and at week 3, the treating physician presumablychanges the treatment protocol (such as again assisted by the bestpractices and predictive algorithm components previously described), theresult being that succeeding linear component (at 784 for weeks three tofive, at 786 for weeks five to eight, and 788 for weeks eight to nine)correspond to a quick visual confirmation for the benefit of thephysician/patient/employer, etc, as to the efficacy of the subsequenttreatment protocols concluding in the return to work event. In thisfashion, the injured worker will utilize the module to describe theinjury details (typically during the first physician visit), record thesymptoms associated with each subsequent visit and record ongoingfunctional metrics regularly during each subsequent appointment (orencounter). For purposes of calculation, the graphical datum points areunderstood to generally correspond to an averaging of all of the duties(A-G) for a given time interval, understanding that the ranges for eachspecific duty at each given interval will vary and a composite oraverage datum score (as between current and goal abilities) is desiredfor determining general improvement of function (as further defined bythe upward angle of the graphical portions 784, 786 and 788 terminatingin the achievement/triggering of the back to work event.

As described, the advantages of the workman compensation module (FIGS.23-44) provide for all of the employer/payer, the physician (PCP orother therapist) and the injured worker/patient to be able to utilizethe same in order to monitor case progress and worker function, toapprove or deny treatment options, to open or close claims, and tomaintain record keeping with Electronic Injury Record (EIR) featuresassociated with existing software for handling such workman compensationclaims. In this fashion, the workman compensation module can beconfigured to interface, to the extent necessary, with existingelectronic software associated with previously existing workmancompensation electronic claims modules (much of which is limited to pdfscanning of existing paper forms with little else in regards toelectronic interface-ability or functionality).

Proceeding now to FIGS. 45-51, a further related rehabilitation moduleis presented, such as not limited to a worker injury event but alsoincluding any injury event associated with a typical accountable careorganization (generally defined as any of a provider network aspreviously identified, insurer, or other payee) in a general healthapplication is provided for establishing and tracking a patient'sfunctional (FEM) measurement score. As with the workman compensationmodule, the rehabilitation module integrates the establishment ofcurrent conditions, achievable goals, and time based tracking of thepatient treatment (including time elapsed changes in response to flatline response indicating a non-effective treatment plan) in order todefine a patient goal outcome and to optimize real time treatment andprogress tracking to that goal. To this end, many of the featurespreviously described, including the establishment of the ACO/payer withbest practices model, the customizable management pathways, the trainingand assigning of care providers, etc., is repeated from the previouslydescribed workman compensation variant such that repetitive descriptionis not required.

The above stated, FIG. 45, subdivided into subset screens 45A &45B,presents a first rehabilitation setting input screen, generally at 790,according to a further module and providing a series of patient entryfields such as for each of prior function, current function and goalfunction. These include in the illustrated embodiment for each of “A.Self Care” (at 792), “B. Sphinctor Control” (at 794), “C. Transfers” (at796), “D. Locomotion” (at 798), “E. Communication” (at 800), and “F.Social Cognition” (at 802).

As indicated above, an effort rating is provided (see percentagegradations for each of 100+ (at 804 for Independent, 806 for ModifiedIndependent and 808 for Supervision Independent), 75+ (at 810), 50+ (at812), 25+ (at 814) and <25 (at 816) for each of discrete CurrentFunction 811, Goal Function 813 and Prior Function 815 subset headingsunder each of A-F (792-802). The various subheadings also includecomment and edit fields as appropriate and which enable the patient toinput or supply necessary information for setting up the subsequentmodule screens. See also patient Yes/No queries 818-826 for such as “ispatient willing to be in an in-patient rehab (at 818), a sub-acute rehab(at 820), does patient have cognition to follow therapy instructions (at822), can patient sit for more than an hour in a chair (at 824), doespatient have social support at home (at 826). Finally, field 828provides for entering all acute diagnosis that the patient is activelybeing treated for, with add button 830. In this manner, both currentfunction 832 and goal function 834 are listed with a difference betweencorresponding to a rehab functional gap 836. Submit button 838 isclicked to proceed to the next screens

FIGS. 46-47 are rehabilitation setting screens, respectively at 840 and842, depicting ranges in current, prior and goal function taken form theinput screen of FIG. 45 and for use in determining metric performanceranges between total physical assist and independent. For each display,a range of variance between Prior, Goal and Current functions is shownfor any selected subset of ADL functions (see again at 792, 796 and 798)and for each of Inpatient Rehab Setting 844. Subacute Rehab Setting 846,Home Care Rehab Setting 848. Out Patient Rehab Setting 850 and None 852.Also shown are drop down menus for each of Range, at 854 with +856 and−858 tabs, as well as ADL drop down menu 860 (e.g. again designatingbetween Self Care and Social Cognition).

FIGS. 48A and 48B collectively depict a succeeding rehabilitation lengthof stay input screen, generally at 862 and corresponding largely to theinputs of screen 790 of FIG. 45, contrasting current ability to goalability and with the objective of establishing determined goals forachieving a maximum possible level of patient independence for each ofself-care 792, sphincter control 794, transfers 796, locomotion 798,communication 800 and social cognition 802. The metrics of FIG. 48assist in estimating an anticipated length of stay of the patient usingthe same general algorithms as in the previous modules. Add button 864again cumulates the current and goal function variables (at 832 and 834)in order to determine a rehab functional gap 836, with submit button 866recording the information and advancing the module to the next screen.

FIGS. 49-51 present a series of overlapping and time elapsed treatmentand rehab length of stay screens, respectively at 868, 870 and 872,which track the inter-ranges and adjustment/progress established betweeneach of the current function 815, goal function 813 and prior function811 variables, with the objective being to close or eliminate the rangesover a time variable extending from date of admission 874, succeedingdates D3 876, D5 878, D9 880, D12, 882, D14 884 (compare date of injuryas in workman comp module) and date of discharge 886 (compare further todate of return to work in prior module). Gap 888 column also provides adiminishing numerical variable (compare at 18 for Admission 874 to 0 atDischarge 886) which corresponds to the general closing of the rangesfor each Function A-F 792-802.

Similar to FIG. 44, a graphical depiction (generally at 890) is providedfor determining time interval components including each of 892(Admission 874 to D3 876), 894 (D3 876 to D5 878), 896 (D5 878 to D9880) denoting lack of improvement and necessitating a change intreatment, 898 (D9 880 to D12 882), 900 (D12 882 to D15 884) and,finally at 902 for D15 884 to Discharge 886. As with the workman compmodule, the upward angle of the interval to interval graphicalcomponents is generally understood to correspond to the overallimprovement of the patient in response to the treatment protocolsprescribed according to the modules disclosed herein and concluding inthe metrics of ADL's (see again 792, 794, 796, et seq.) between Prior,Current and Goal functions eventually closing to no range (at time ofDischarge).

As with the previously disclosed variants, the above screen displays andprotocols associated with the modules of FIGS. 23-44 and 45-51 can beintegrated into subroutines associated with the non-transitory computerwriteable medium, such as which is usable with a processor driven devicefor use in the treatment of an injured worker by a care provider, and inthe instance of a worker further being involved in a workmancompensation claim with an employer or payer.

A listing of such subroutines can include each of a first subroutine forassembling a provider network incorporating a best practices model (seeagain FIGS. 1-17) in the form of a database interfacing with theprocessor device and which presents series of treatment optionsassociated with a given type of service, along with a fee scheduleincentivizing the care provider in the achievement of a best functionaloutcome. A second subroutine is provided for training a plurality of thecare providers in one or more of a series of medical related diagnosisand treatment programs consistent with the objectives of the firstsubroutine, the second subroutine further including establishing one ormore management pathways which are customizable by the provider networkand through establishing a questioning protocol for modifying orcustomizing a base algorithm for any one or more of a variety oftreatment sub-species (see again FIGS. 18-22).

A third subroutine in the computer model may also include use by asupervisor designated by the employer/payer and which, upon theoccurrence of an injury event, provides input of both workerbiographical and detail of injury, with a fourth subroutine providing anassignment, by the provider network, of the care provider (such beingthe doctor in the area who is best suited for treating the patient asdetermined by screen illustration of FIG. 25). A fifth subroutine, uponan initial visit of the injured worker with the care provider, providesfor confirmation by the worker of details previously provided by thesupervisor and for the inputting of additional information and/ordetails surrounding the injury event.

A sixth subroutine can establish, by the worker with or without theassistance of the care provider, an electronic initial injury detailchart including at least one of a pictorial representation of a humanform, along with inputs for symptoms relating to the injury eventincluding type and intensity of pain. A seventh subroutine synthesizesall of the preceding subroutines in the establishment of a symptoms andtreatment catalog over a duration of time extending from the injuryevent to an eventually determined end event corresponding to a recoveryby the worker of a level of ability and function necessary fortriggering a return to work event. Finally, an eighth subroutineprovides for iterative treatment of the worker and updating the symptomsand treatment catalog, such occurring at determined time intervalsfollowing the injury event until the eventually determined end event.

Additional related subroutines include for determining, between the careprovider, worker and employer/payer, a set of goals for achievement bythe injured worker in triggering the return to work event. Theafore-mentioned sixth subroutine may also include front and backpictorial depictions of a human form (see again FIG. 28 et seq.), thesymptom inputs further including a listing of any of an aching pain,stabbing pain, burning pain or a numbness/tingling, along with either ofa color or numerical intensity code.

Further consistent with the afore-described embodiments, a tenth workerability input subroutine can be provided, occurring between the fifthand seventh subroutines, and listing a number of typical dutiesassociated with a job of the worker, and for which the worker provides acurrent ability input. The current ability input of the tenth subroutinemay also include a listing a point score for each duty as tied to anyone of a minimum effort, moderate effort, severe effort, extreme effortand unable to perform, an accumulation of the points totaling a workercurrent ability.

Additional features of the eighth subroutine include a time intervalcomparison of the current ability and goals and corresponding to bothtreatment and changes in treatment derived from the first and secondsubroutines. Other features include synthesizing the worker abilityinput subroutine with the seventh and eighth subroutines in order tocreate an eleventh subroutine for determining, for each time interval, arange between worker inputted current ability and goal ability for eachidentified job duty.

Yet additional inputs include a twelfth subroutine for graphing asuccession of time interval data points, each corresponding to anaverage of a current worker ability for the identified job duties, thecare provider comparing an angle of inclination of the graph with thetreatment protocols provided in the best practices model of the firstsubroutine and the management pathways of the second subroutine in thecontinued treatment of the worker according to the eighth subroutine.

As to the related rehabilitation module, a listing of the associatedsubroutines can similarly include a first subroutine for assembling aprovider network incorporating a best practices model in the form of adatabase interfacing with the processor device and which presents seriesof treatment options associated with a given type of service, along witha fee schedule incentivizing the care provider in the achievement of abest functional outcome, with a second subroutine for training aplurality of the care providers in one or more of a series of medicalrelated diagnosis and treatment programs consistent with the objectivesof the first subroutine, the second subroutine further includingestablishing one or more management pathways which are customizable bythe provider network and through establishing a questioning protocol formodifying or customizing a base algorithm for any one or more of avariety of treatment sub-species.

A third subroutine is provided for entering or synthesizing patientinformation including biographical and nature/type of conditionassociated with an event date, with a fourth subroutine for assignment,by the provider network, of a care provider for the treatment of thepatient.

Additional inputs include a fifth rehabilitation setting inputsubroutine for establishing, by the patient with or without theassistance of the care provider, a listing of scaled efforts rangingindependent to total physical assist and associated with a listing ofpatient ADL functions, such determinative of a present or futurerehabilitative setting as recommended to the provider network. A sixthsubroutine synthesizing all of the preceding subroutines in theestablishment of a treatment and rehabilitation catalog over a durationof time extending from the event date to an eventually determined endevent corresponding to an eventual final degree of recovery by thepatient of a level of ability and function associated with an endrehabilitation setting. Finally, a seventh subroutine provides foriteratively treating the patient and updating the symptoms and treatmentcatalog, such occurring at determined time intervals following the eventdate until the eventually determined end date.

As to the rehabilitation module, additional inputs include an eighthrehabilitation subroutine for determining, between the care provider,patient and provider network, a set of goals for achievement by thepatient in satisfying an established criteria for a given rehabilitationsetting ranging from inpatient, subacute, home care, outpatient or none.The seventh subroutine can further include a time interval comparison ofthe current ability and goals and corresponding to both treatment andchanges in treatment derived from the first and second subroutines

Additional inputs include synthesizing the rehabilitation setting inputsubroutine with the sixth and seventh subroutines in order to create aninth rehab setting subroutine for determining, for each time interval,a range between patient inputted prior function, current function andgoal function for each identified ADL function. An eighth subroutineinput provides for graphing a succession of time interval data points,each corresponding to an average of a patient ability for the identifiedADL functions, the care provider comparing an angle of inclination ofthe graph with the treatment protocols provided in the best practicesmodel of the first subroutine and the management pathways of the secondsubroutine in the continued treatment of the patient according to theseventh subroutine.

Numerous advantages associated with the present system include each ofenabling patients and healthcare providers to input function in asimplified, accurate way, to create a date stamped and visuallydisplayed record for patient function, such being displayed in anexpanded or focused time chart, enabling medical providers to easilyconsume, to synthesize medical data, and take effective actions toimprove outcomes, to simplify and standardize communications betweenpatient, providers and healthcare managers/payers, to create a visualdisplay of a patient's functional status and to visually identify gapsbetween current and desired/goal functions, and to accurately report thepatient function, with savings incurred to both the provider andpatient.

Other advantages associated with the symptoms/input catalog includesavings in time and increased accuracy by avoiding asking and answeringof duplicative questions and duplicative inputting of descriptions ofpatient symptoms, creating a date stamped visually displayed record forthe patient's symptoms which is displaced in both expanded or focusedtime charts, enabling the medical providers to easily consume andsynthesize medical data and take effective actions to improve outcomes.Other advantages include simplifying and standardizing communicationsbetween the patient, provider and healthcare managers/payers, creating avisual display of the patient's symptoms and visually identifying gapsbetween the current and desired or goal symptoms and, finally,accurately reporting with time savings to all parties.

Having described my invention, other and additional embodiments willbecome apparent to those skilled in the art to which it pertains andwithout deviating from the scope of the appended claims.

I claim:
 1. A non-transitory software based algorithmic medium usablewith a processor driven device for use in the treatment of an injuredworker by a care provider, the worker further being involved in aworkman compensation claim with an employer or payer, comprising: afirst subroutine for assembling a provider network incorporating a bestpractices model in the form of a database interfacing with the processordevice and which presents series of treatment options associated with agiven type of service, along with a fee schedule incentivizing the careprovider in the achievement of a best functional outcome; a secondsubroutine for training a plurality of the care providers in one or moreof a series of medical related diagnosis and treatment programsconsistent with the objectives of the first subroutine, said secondsubroutine further including establishing one or more managementpathways which are customizable by the provider network and throughestablishing a questioning protocol for modifying or customizing a basealgorithm for any one or more of a variety of treatment sub-species; athird subroutine for use by a supervisor designated by theemployer/payer and which, upon the occurrence of an injury event,provides input of both worker biographical and detail of injury; afourth subroutine for assignment, by the provider network, of the careprovider; a fifth subroutine which, upon an initial visit of the injuredworker with the care provider, provides for confirmation by the workerof details previously provided by the supervisor and for the inputtingof additional information and/or details surrounding the injury event; asixth subroutine for establishing, by the worker with or without theassistance of the care provider, an electronic initial injury detailchart including at least one of a pictorial representation of a humanform, along with inputs for symptoms relating to the injury eventincluding type and intensity of pain; a seventh subroutine forsynthesizing all of the preceding subroutines in the establishment of asymptoms and treatment catalog over a duration of time extending fromthe injury event to an eventually determined end event corresponding toa recovery by the worker of a level of ability and function necessaryfor triggering a return to work event; and an eighth subroutine foriteratively treating the worker and updating the symptoms and treatmentcatalog, such occurring at determined time intervals following theinjury event until the eventually determined end event.
 2. Thenon-transitory software based algorithmic medium of claim 1, furthercomprising a ninth subroutine for determining, between the careprovider, worker and employer/payer, a set of goals for achievement bythe injured worker in triggering the return to work event.
 3. Thenon-transitory software based algorithmic medium of claim 2, said sixthsubroutine further comprising front and back pictorial depictions of ahuman form, said symptom inputs further comprising listing of any of anaching pain, stabbing pain, burning pain or a numbness/tingling, alongwith either of a color or numerical intensity code.
 4. Thenon-transitory software based algorithmic medium of claim 1, furthercomprising a tenth worker ability input subroutine, occurring betweenthe fifth and seventh subroutines, and listing a number of typicalduties associated with a job of the worker, and for which the workerprovides a current ability input.
 5. The non-transitory software basedalgorithmic medium of claim 4, said current ability input of the tenthsubroutine further comprising listing a point score for each duty astied to any one of a minimum effort, moderate effort, severe effort,extreme effort and unable to perform, an accumulation of the pointstotaling a worker current ability.
 6. The non-transitory software basedalgorithmic medium of claim 5, said eighth subroutine further comprisinga time interval comparison of said current ability and goals andcorresponding to both treatment and changes in treatment derived fromthe first and second subroutines.
 7. The non-transitory software basedalgorithmic medium of claim 6, further comprising synthesizing saidworker ability input subroutine with said seventh and eighth subroutinesin order to create an eleventh subroutine for determining, for each timeinterval, a range between worker inputted current ability and goalability for each identified job duty.
 8. The non-transitory softwarebased algorithmic medium of claim 7, further comprising a twelfthsubroutine for graphing a succession of time interval data points, eachcorresponding to an average of a current worker ability for theidentified job duties, the care provider comparing an angle ofinclination of the graph with the treatment protocols provided in thebest practices model of the first subroutine and the management pathwaysof the second subroutine in the continued treatment of the workeraccording to the eighth subroutine.
 9. A non-transitory software basedalgorithmic medium usable with a processor driven device for use in thetreatment and rehabilitation of a patient covered by a provider network,comprising: a first subroutine for assembling a provider networkincorporating a best practices model in the form of a databaseinterfacing with the processor device and which presents series oftreatment options associated with a given type of service, along with afee schedule incentivizing the care provider in the achievement of abest functional outcome; a second subroutine for training a plurality ofthe care providers in one or more of a series of medical relateddiagnosis and treatment programs consistent with the objectives of thefirst subroutine, said second subroutine further including establishingone or more management pathways which are customizable by the providernetwork and through establishing a questioning protocol for modifying orcustomizing a base algorithm for any one or more of a variety oftreatment sub-species; a third subroutine for entering or synthesizingpatient information including biographical and nature/type of conditionassociated with an event date; a fourth subroutine for assignment, bythe provider network, of a care provider for the treatment of thepatient; a fifth rehabilitation setting input subroutine forestablishing, by the patient with or without the assistance of the careprovider, a listing of scaled efforts ranging independent to totalphysical assist and associated with a listing of patient ADL functions,such determinative of a present or future rehabilitative setting asrecommended to the provider network; a sixth subroutine for synthesizingall of the preceding subroutines in the establishment of a treatment andrehabilitation catalog over a duration of time extending from the eventdate to an eventually determined end event corresponding to an eventualfinal degree of recovery by the patient of a level of ability andfunction associated with an end rehabilitation setting, and a seventhsubroutine for iteratively treating the patient and updating thesymptoms and treatment catalog, such occurring at determined timeintervals following the event date until the eventually determined enddate.
 10. The non-transitory software based algorithmic medium of claim9, further comprising an eighth rehabilitation subroutine fordetermining, between the care provider, patient and provider network, aset of goals for achievement by the patient in satisfying an establishedcriteria for a given rehabilitation setting ranging from inpatient,subacute, home care, outpatient or none.
 11. The non-transitory softwarebased algorithmic medium of claim 10, said seventh subroutine furthercomprising a time interval comparison of said current ability and goalsand corresponding to both treatment and changes in treatment derivedfrom the first and second subroutines.
 12. The non-transitory softwarebased algorithmic medium of claim 11, further comprising synthesizingsaid rehabilitation setting input subroutine with said sixth and seventhsubroutines in order to create a ninth rehab setting subroutine fordetermining, for each time interval, a range between patient inputtedprior function, current function and goal function for each identifiedADL function.
 13. The non-transitory software based algorithmic mediumof claim 12, further comprising an eighth subroutine for graphing asuccession of time interval data points, each corresponding to anaverage of a patient ability for the identified ADL functions, the careprovider comparing an angle of inclination of the graph with thetreatment protocols provided in the best practices model of the firstsubroutine and the management pathways of the second subroutine in thecontinued treatment of the patient according to the seventh subroutine.